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Identification of novel off targets of baricitinib and tofacitinib by machine learning with a focus...

Identification of novel off targets of baricitinib and tofacitinib by machine learning with a focus...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_b90a0be877b546d1a81f84dd7bbe2044

Identification of novel off targets of baricitinib and tofacitinib by machine learning with a focus on thrombosis and viral infection

About this item

Full title

Identification of novel off targets of baricitinib and tofacitinib by machine learning with a focus on thrombosis and viral infection

Publisher

London: Nature Publishing Group UK

Journal title

Scientific reports, 2022-05, Vol.12 (1), p.7843-7843, Article 7843

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

As there are no clear on-target mechanisms that explain the increased risk for thrombosis and viral infection or reactivation associated with JAK inhibitors, the observed elevated risk may be a result of an off-target effect. Computational approaches combined with in vitro studies can be used to predict and validate the potential for an approved dr...

Alternative Titles

Full title

Identification of novel off targets of baricitinib and tofacitinib by machine learning with a focus on thrombosis and viral infection

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_b90a0be877b546d1a81f84dd7bbe2044

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_b90a0be877b546d1a81f84dd7bbe2044

Other Identifiers

ISSN

2045-2322

E-ISSN

2045-2322

DOI

10.1038/s41598-022-11879-1

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